1,720,974 research outputs found
Boltzmann machines as generalized hopfield networks: A review of recent results and outlooks
Full text linkThe Hopfield model and the Boltzmann machine are among the most popular examples of neural networks. The latter, widely used for classification and feature detection, is able to efficiently learn a generative model from observed data and constitutes the benchmark for statistical learning. The former, designed to mimic the retrieval phase of an artificial associative memory lays in between two paradigmatic statistical mechanics models, namely the Curie-Weiss and the Sherrington-Kirkpatrick, which are recovered as the limiting cases of, respectively, one and many stored memories. Interestingly, the Boltzmann machine and the Hopfield network, if considered to be two cognitive processes (learning and information retrieval), are nothing more than two sides of the same coin. In fact, it is possible to exactly map the one into the other. We will inspect such an equivalence retracing the most representative steps of the research in this field
From knowledge to impact. An investigation of the commercial outcomes of academic engagement with industry
No full textThe multifaceted issues regarding university-industry relations are an increasing focus of attention of both scholars and practitioners, as a means of enhancing current knowledge transfer practices and policies. One of the central questions is whether and how the mechanisms underlying different types of university-industry collaborations (collaborative research, contract research, consulting) influence universities’ research commercialisation outcomes (patenting, licensing, spin-off generation). Results of six negative binomial models in Generalized Estimating Equations based on longitudinal panel data on Italian universities, reveal that while collaborative research with industry leads to an increase in patenting activities and spin-off generation, contract research and consulting boost licensing opportunities. Results also reveal complementarities between different types of university-industry linkages, fostering all the types of research commercialisation outcomes. Managerial and policy implications are discussed at the end of this paper
Managing open innovation projects: an evidence-based framework for SMEs and large companies cooperation
No full textHow can joint open innovation (OI) projects between small and medium-sized enterprises (SMEs) and large companies (LCs) be effectively managed? This study aims to try to answer this research question with a focus on the critical success factors (CSFs) of such cooperation.
Based on 40 semi-structured interviews with Italian SMEs and LCs engaged in various industries, 20 open OI projects involving SMEs and LCs are investigated using a reflexive thematic analysis, a methodology involving both deductive and inductive approaches.
Fifteen CSFs grouped into seven categories emerge from the analysis of joint OI projects between SMEs and LCs. Among them, shared leadership, dynamic decision-making and priority setting emerge as essential elements at the basis of the proposed SMEs–LCs cooperation in joint OI projects that were not sufficiently addressed by prior studies.
To the best of the authors’ knowledge, this study is the first to provide an evidence-based framework for managing joint OI projects between SMEs and LCs. Relatedly, this study links the practices and most recurring CSFs that facilitate such cooperation
Storing, learning and retrieving biased patterns
No full textThe formal equivalence between the Hopfield network (HN) and the Boltzmann Machine (BM) has been well established in the context of random, unstructured and unbiased patterns to be retrieved and recognised. Here we extend this equivalence to the case of “biased” patterns, that is patterns which display an unbalanced count of positive neurons/pixels: starting from previous results of the bias paradigm for the HN, we construct the BM's equivalent Hamiltonian introducing a constraint parameter for the bias correction. We show analytically and numerically that the parameters suggested by equivalence are fixed points under contrastive divergence evolution when exposed to a dataset of blurred examples of each pattern, also enjoying large basins of attraction when the model suffers of a noisy initialisation. These results are also shown to be robust against increasing storage of the models, and increasing bias in the reference patterns. This picture, together with analytical derivation of HN's phase diagram via self-consistency equations, allows us to enhance our mathematical control on BM's performance when approaching more realistic datasets
Heterogeneous determinants of SMEs growth. A comparative look at open and closed innovation strategies
No full textOpen Innovation 2.0 Strategies and New Open Business Models. Case Studies from Europe
No full textOpen Innovation 2.0 Strategies and New Open Business Models. Case Studies from Europ
Exploring circular consumption: Circular attitudes and their influence on consumer behavior across the product lifecycle
No full textThis study explores the dynamic and multidimensional domain of circular consumption, emphasizing the relevance of a lifecycle perspective in understanding consumer behaviors within the circular economy. Moving beyond prior research that predominantly focused on specific actions such as recycling or purchasing second-hand products, we advocate for a more comprehensive understanding of consumer choices throughout a product's lifecycle. Drawing on attitudes theory, we employ item response theory (IRT) models to unveil latent attitudes reflecting diverse circular consumer behaviors. These attitudes, inferred from manifested actions across different product lifecycle stages, include environmental-centric, resource-centric, and societal-centric circular attitudes. The study involves a representative sample of 5,124 respondents across five European countries. Our findings underscore the complexity of consumer motivations in the circular economy, revealing distinct links between circular attitudes and behaviors. This research contributes to a nuanced understanding of circular consumption, emphasizing the importance of a lifecycle approach, and driving the development of robust measurement scales for circular consumer actions
Open for innovation: An improved measurement approach using item response theory
No full textDrawing on the theoretical foundations of attitudes and their role in the decision process underlying open innovation (OI) adoption, this study conveys a new perspective of examining firm-level openness as a construct. Based on Item Response Theory, a family of latent trait models rooted in psychology, and using data from the German section of the Community Innovation Survey, we advance a nuanced measure of openness capturing the firm-level attitudes toward external knowledge reception, going beyond current measures focusing on its attributed effects. This approach, based on an implicit attitude measure, allows us to assess the types of OI practices characterizing firms with different value structures (i.e., higher/lower attitudes toward external knowledge), thus offering a more reliable comparison of firms along the openness continuum. A systematic comparison with the widely used measures of external search breadth and depth shows that higher openness is not merely reflected by a higher number (or a more intensive use) of external knowledge sources but by a higher attitude toward complex search patterns, typically implying more challenging OI activities. The proposed construct has strong external validity, as it reflects the key theoretical features of openness and its paradoxes - an inverted U-shaped relationship with innovation performance. The results of this study provide both theoretical and practical implications
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